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Record W2010441927 · doi:10.1016/j.gheart.2014.08.003

Acute Respiratory Distress Syndrome in the Global Context

2014· review· en· W2010441927 on OpenAlexaff
Egide Buregeya, Robert Fowler, Daniel Talmor, Théogène Twagirumugabe, Willy Kiviri, Elisabeth D. Riviello

Bibliographic record

VenueGlobal Heart · 2014
Typereview
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsSunnybrook Hospital
Fundersnot available
KeywordsMedicineChecklistContext (archaeology)Global healthObservational studySystematic reviewFamily medicinePublic healthMedical educationMEDLINEPathologyPolitical sciencePsychology

Abstract

fetched live from OpenAlex

Acute respiratory distress syndrome (ARDS) is a clinically defined syndrome of hypoxia and bilateral pulmonary infiltrates due to inflammatory pathways triggered by pulmonary and nonpulmonary insults, and ARDS is pathologically correlated with diffuse alveolar damage. Estimates of ARDS's impact in the developed world vary widely, with some of the discrepancies attributed to marked differences in the availability of intensive care beds and mechanical ventilation. Almost nothing is known about the epidemiology of ARDS in the developing world, in part due to a clinical definition requiring positive pressure ventilation, arterial blood gases, and chest radiography. Current frameworks for comparing the epidemiology of death and disability across the world including the GBD (Global Burden of Disease Study) 2010 are ill-suited to quantifying critical illness syndromes including ARDS. Modifications to the definition of ARDS to allow a provision for environments without the capacity for positive pressure ventilation, and to allow for alternate diagnostic techniques including pulse oximetry and ultrasound, may make it possible to quantify and describe the impact of ARDS in the global context.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.031
GPT teacher head0.374
Teacher spread0.343 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations35
Published2014
Admission routes1
Has abstractyes

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